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---
license: mit
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: IMDB_XLNET_5E
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
split: train
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.94
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# IMDB_XLNET_5E
This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3195
- Accuracy: 0.94
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3192 | 0.63 | 50 | 0.2033 | 0.94 |
| 0.196 | 1.27 | 100 | 0.2036 | 0.9467 |
| 0.1651 | 1.9 | 150 | 0.2106 | 0.9267 |
| 0.0628 | 2.53 | 200 | 0.3531 | 0.92 |
| 0.0865 | 3.16 | 250 | 0.2186 | 0.9533 |
| 0.0436 | 3.8 | 300 | 0.2718 | 0.9533 |
| 0.0254 | 4.43 | 350 | 0.3195 | 0.94 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1
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